Claudia Cerbai                            

Thesis project title: to be defined

abstract

International partner:  to be defined
Supervisor: Fabio Bianconi
Internal co-supervisor: Marco Filippucci, Nicola Cavalagli
International supervisor:  -
e-mail:  

Jessica Di Mario

Thesis project title: to be defined

abstract

International partner:  to be defined
Supervisor: Giovanni Gigliotti
International co-supervisor:  -
e-mail:  
 

Eleonora Dottorini

Thesis project titleto be defined

abstract

International partner: to be defined
Supervisor: Valeria Menchetelli
International Supervisor:  -
e-mail:  

Livia Fabbretti                       

Thesis project title: Study and implementation of innovative methods for seismic monitoring and damage detection in strategic public buildings.

abstract

International partner: to be defined
Supervisor: Marco Breccolotti
Internal co-supervisor Filippo Ubertini
International Supervisor:  -
e-mail:  
 

Debora Falocci                       

Thesis project title: to be defined

abstract

International partner: to be defined
Supervisor: Silvia Meniconi
Internal co-supervisor: Caterina capponi
International Supervisor:  -
e-mail:  
 

Gregorio Gazzetta

Thesis project titleto be defined

abstract

International partner: to be defined
Supervisor: Silvia Meniconi
Internal co-supervisor: Paolina Bongioannini Cerlini
International Supervisor:  -
e-mail:  
 

Pasquale Guarino

Thesis project title: to be defined

abstract

International partner: University of Granada (Spain)
Supervisor: Filippo Ubertini
Internal co-supervisor: Andrea Meoni
International Supervisor:

Enrique Garcia-Macias

e-mail:  
 

Francesco Leopardi

Thesis project titleto be defined

abstract

International partner:  -
Supervisor: Carla Saltalippi
Internal co-supervisor: Jacopo Dari, Stefania Camici
International Supervisor: to be defined
e-mail:  
 

Francesco Mariani

Thesis project title: Handling uncertainties in Safety Assessment of Existing Bridges - SAFER

abstract:

One of the main challenges in modern civil engineering is the multi-risk analysis of infrastructures aimed at optimizing maintenance interventions and ensuring sustainable and resilient management of transport networks. The case of bridges is particularly relevant due to the high number of structures requiring maintenance and their exposure to evolving (aging of materials) and natural (landslides, earthquakes, and floods) phenomena, prompting the recent issuance of specific regulatory measures. In this context, uncertainties regarding the environment in which the structures are located and their actual behavior play a crucial role.
Risk analyses involve the thorough evaluation of the safety of structures for which specific critical issues have been identified at a lower hierarchical level. Despite having regulatory provisions (e.g. Eurocodes or Italian NTC2018), there is a lack of a systematic approach to managing and mitigating the impact of uncertainties on the outcomes of such evaluations. Consequently, there are no significant experiences and specific indications regarding the execution of surveys, structural investigations, and instrumental monitoring aimed at improving the reliability of safety assessment, despite numerous recent contributions on the subject. In this context, digital innovation can play a decisive role in the automation and standardization of processing processes, as well as in the evaluation of evolving phenomena. Overall, it is necessary to address the problem of accurately assessing the safety of existing bridges in a severely uncertain context and employ innovative strategies, such as those based on Bayesian inference, to manage and mitigate the impact of uncertainties on safety assessment outcomes by utilizing available information based on in-situ surveys and instrumental monitoring systems.

International partner: Trinity College Dublin - Ireland
Supervisor: Ilaria Venanzi
Internal co-supervisor: Filippo Ubertini, Laura Ierimonti
International Supervisor: Alan O' Connor
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
 

Michele Mattiacci

Thesis project title: Advanced strategies for strain-based health monitoring of masonry structures

abstract:

Masonry structures, predominant in Europe's built heritage, face preservation challenges due to material degradation and seismic hazards. Assessing the structural integrity of masonry buildings is often a challenging task, especially in the case of historical structures. This is mainly because features such as irregular geometry, heterogeneity of masonry, material ageing, and damages suffered over the years due to unexpected loading conditions (like earthquakes and foundation settlements, to name a few) introduce uncertainties in determining their actual structural response.

Historic masonry buildings preservation throughout Europe is an immediate priority, necessitating suitable Structural Health Monitoring (SHM) solutions that should establish a connection between measured data related to the structure's in-service response and its residual load-bearing capacity and structural integrity. As of now, the widespread implementation of SHM systems in masonry structures remains limited. This is primarily due to challenges associated with off-the-shelf sensors that face issues related to scalability, durability, transmission, and high costs. Considering the above, smart materials could constitute a cutting-edge technology to overcome such limitations related to the practical implementation of SHM systems in masonry buildings. In addition to this, the analysis of data collected by sensors made from these innovative materials using AI and machine learning algorithms can enable automated earthquake-induced damage identification, quantification, and localization. The proposed research project aims to establish a novel methodology for promptly assessing the structural condition of masonry structures following a hazardous event, leveraging innovative sensing technology based on smart materials, Artificial Intelligence, and numerical modeling.

International partner: Princeton University
Supervisor: Filippo Ubertini
Internal co-supervisor: Andrea Meoni
International Supervisor: Branko Glisic
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
 

Carlos Eugenio Moureira Desousa

Thesis project title: to be defined

abstract

International partner:  -
Supervisor: Marco Breccolotti
Internal co-supervisor: Filippo Ubertini
International Supervisor: to be defined
e-mail:  
 

Martina Natali

Thesis project title: Integrated use of radar backscatter observations, machine learning and land surface modeling to improve soil and vegetation dynamics in Mediterranean agroforestry systems

abstract:

he proposed doctoral dissertation aims to enhance the understanding of soil-water-vegetation interactions in Mediterranean agroforestry systems through the integrated use of radar backscatter observations, machine learning, and land surface modeling. The research focuses on addressing the challenges posed by climate-induced water stress in rain-fed, natural ecosystems, which increasingly affects photosynthesis and evapotranspiration processes. By leveraging high-resolution, multi-frequency and multi-polarization backscatter data from different satellite platforms, and assimilating these into the Noah-Multiparameterization Land Surface Model (Noah-MP), the project seeks to improve predictions of vegetation dynamics and water stress. The methodology involves collecting remote sensing and in-situ data across selected sites in Italy, equipped with multiple instruments for measuring soil moisture, vegetation and carbon fluxes, applying machine learning to establish relationships between radar data and biophysical variables, and integrating data into the Noah-MP model through data assimilation techniques. This approach is expected to enhance the model's accuracy in simulating soil moisture, vegetation water content, and overall ecosystem responses to environmental changes. The research outcomes will offer significant implications for forestry ecosystems' services, agricultural practices and water resource management in Mediterranean environments.

International partner:  -
Supervisor: Alessia Flammini
Internal co-supervisor: Jacopo Dari, Cristian Massari
International Supervisor: to be defined
e-mail:  
 

Yariv Portnoy

Thesis project title: to be defined

abstract

International partner:  -
Supervisor: Maurizio Natali
Internal co-supervisor: to be defined
International Supervisor: to be defined
e-mail:  
 

Sara Prapotnich

Thesis project title: to be defined

abstract

International partner:  -
Supervisor: Silvia Meniconi
Internal co-supervisor: Caterina Capponi
International Supervisor: to be defined
e-mail:  
 

Waqas Qayyum

Thesis project title: to be defined

abstract

International partner: University of Granada (Spain)
Supervisor: Nicola Cavalagli
Internal co-supervisor: Filippo Ubertini, Massimiliano Gioffré, Paolo Neri
International Supervisor: Enrique Garcia-Macias
e-mail:  
 

Arash Rahimi

Thesis project title: to be defined

abstract

International partner:  -
Supervisor: Ilaria Venanzi
Internal co-supervisor: Filippo Ubertini, Laura Ierimonti
International Supervisor: to be defined
e-mail:  
 

Mehran Shahpari

Thesis project title: to be defined

abstract

International partner:  -
Supervisor: Massimiliano Gioffré
Internal co-supervisor: Chiara Pepi
International Supervisor: to be defined
e-mail:  
 

Asad Ullah

Thesis project title: to be defined

abstract

International partner:  -
Supervisor: Piergiorgio Manciola
Internal co-supervisor: Diana Salciarini, Filippo Ubertini, Nicola Cavalagli
International Supervisor: Andrea Meoni
e-mail:  
 

Sousa Israel (affiliation with the national doctorate "Defence from natural risks and ecological transition of buildings" with administrative headquarters at the University of Catania)

Thesis project title: to be defined

abstract

International partner: Iowa State University (USA)
Supervisor: Antonella D'Alessandro
Internal co-supervisor: Filippo Ubertini
International Supervisor: Simon LaFlamme
e-mail: